nichenetr (version 0.1.0)

add_ligand_popularity_measures_to_perfs: Merge target gene prediction performances with popularity measures of ligands

Description

add_ligand_popularity_measures_to_perfs: Get a data.frame in which the performance measures for target gene prediction of a ligand are merged with the number of times the ligand is mentioned in the Pubmed literature. Serves to investigate popularity bias (i.e. it can be expected that frequenly cited ligands will have better predictive performance because they are better studied).

Usage

add_ligand_popularity_measures_to_perfs(performances, ncitations)

Arguments

performances

A data.frame in which the performance measures for target gene predictions of ligands are denoted

ncitations

A data frame denoting the number of times a gene is mentioned in the Pubmed literature. Should at least contain following variables: 'symbol' and 'ncitations'. Default: ncitations (variable contained in this package). See function get_ncitations_genes for a function that makes this data frame from current Pubmed information.

Value

A data.frame in which the performance measures for target gene prediction of a ligand are merged with the number of times the ligand is mentioned in the Pubmed literature.

Examples

# NOT RUN {
library(dplyr)
weighted_networks = construct_weighted_networks(lr_network, sig_network, gr_network, source_weights_df)
settings = lapply(expression_settings_validation[1:10],convert_expression_settings_evaluation)
ligands = extract_ligands_from_settings(settings)
ligand_target_matrix = construct_ligand_target_matrix(weighted_networks, ligands)
performances = bind_rows(lapply(settings,evaluate_target_prediction,ligand_target_matrix))
# ncitations = get_ncitations_genes()
performances_ligand_popularity = add_ligand_popularity_measures_to_perfs(performances,ncitations)
# }
# NOT RUN {
# }